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[CVPR 2023 Highlight] InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions

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Hello, I'm trying to export a segmentation model to onnx. I updated the core_op to 'DCNv3_pytorch' and i was able to deploy the model and generate the onnx file. But...

我在windows平台尝试调试segmentation里的train.py, 但是遇到了如下问题 ![image](https://user-images.githubusercontent.com/74486453/226152430-2b7ff5bc-34ca-44a0-bcf5-a64e33c5c759.png) 我单步调试后发现当尝试import mmcv时会触发该bug, 但是我已经按照readme安装了该库 我在错误处尝试换gbk编码解释该字符串, 能成功解析 ![image](https://user-images.githubusercontent.com/74486453/226152609-339910ce-4a35-4bb3-b81b-f93d4e76988e.png) 我在全盘搜索了该字符串, 发现它位于安装目录Python\Python39\Lib\site-packages\torch\utils下的cpp_extension.py中 ![image](https://user-images.githubusercontent.com/74486453/226152653-1f5f6b71-807a-4f4e-b520-191d1ad0e30a.png) 我不太清楚是否是环境的问题, 以及是否能在windows上修复该问题 谢谢

Are there any plans to add this model to MMDetection mainline so that more people can discover and use it?

Hi , I'm trying the occupancy prediction model at https://github.com/OpenGVLab/InternImage/tree/master/autonomous_driving/occupancy_prediction but error occurs when I compile the mmdet3d==0.18.1 # recommend cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC...

return F.linear(input, self.weight, self.bias) RuntimeError: mat1 and mat2 shapes cannot be multiplied (2112x1000 and 96x96) 请问这种参数该怎么设置?我的输入的张量形式是(96,1,22,1000)

During handling of the above exception, another exception occurred: Traceback (most recent call last): File "train.py", line 243, in main() File "train.py", line 162, in main cfg.dump(osp.join(cfg.work_dir, osp.basename(args.config))) File "D:\anaconda3\envs\internimage\lib\site-packages\mmcv\utils\config.py",...

请问一下,怎么固定随机种子,让每次跑出来的结果是相同的?

## Purpose - Reduce the deployment difficulty of small-scale visual models using DCNv3 on different devices (using the same precompiled package for downgrading) ## Work - Provide CPU downgrade by...

# Code: import os import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns from sklearn.model_selection import train_test_split from sklearn.metrics import classification_report, confusion_matrix, accuracy_score,...